U.S. patent application number 11/296829 was filed with the patent office on 2006-04-20 for novel ways of assessing metabolic processes.
Invention is credited to Steven M. Watkins.
Application Number | 20060084129 11/296829 |
Document ID | / |
Family ID | 28046949 |
Filed Date | 2006-04-20 |
United States Patent
Application |
20060084129 |
Kind Code |
A1 |
Watkins; Steven M. |
April 20, 2006 |
Novel ways of assessing metabolic processes
Abstract
The present invention provides methods for assessing
contribution of one or more pathways to the biosynthesis of a
metabolite, e.g., a lipid using the levels of the product made and
the metabolite precursors for each pathway.
Inventors: |
Watkins; Steven M.;
(Sacramento, CA) |
Correspondence
Address: |
MORRISON & FOERSTER LLP
755 PAGE MILL RD
PALO ALTO
CA
94304-1018
US
|
Family ID: |
28046949 |
Appl. No.: |
11/296829 |
Filed: |
December 6, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10615966 |
Jul 9, 2003 |
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11296829 |
Dec 6, 2005 |
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10383671 |
Mar 7, 2003 |
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10615966 |
Jul 9, 2003 |
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60363587 |
Mar 11, 2002 |
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60373912 |
Apr 19, 2002 |
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60401684 |
Aug 6, 2002 |
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60424949 |
Nov 8, 2002 |
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60436192 |
Dec 24, 2002 |
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Current U.S.
Class: |
435/15 ;
436/71 |
Current CPC
Class: |
A61K 31/4415 20130101;
A61K 38/27 20130101; C12N 9/1003 20130101; A61K 31/51 20130101;
A61K 31/455 20130101; A61K 31/7076 20130101; A61K 31/519 20130101;
G01N 33/92 20130101; C12Y 201/01017 20130101; G01N 2800/52
20130101; A61P 9/00 20180101; A61P 25/00 20180101; A61K 31/00
20130101; G01N 33/57484 20130101 |
Class at
Publication: |
435/015 ;
436/071 |
International
Class: |
C12Q 1/48 20060101
C12Q001/48; G01N 33/92 20060101 G01N033/92 |
Claims
1. A method for determining the contribution of a pathway to the
biosynthesis of a lipid class comprising determining the level of a
marker composition in a precursor, determining the level of the
marker composition in a lipid class, wherein the precursor is
transformed to the lipid class via a pathway, and wherein the level
of the marker composition in the precursor relative to the level of
the marker composition in the lipid class is indicative of the
contribution of the pathway to the biosynthesis of the lipid
class.
2. A method of determining the contribution of a first pathway and
a second pathway to the biosynthesis of a lipid class comprising
determining P1, wherein P1 is the level of a marker composition in
a first precursor of a lipid class, wherein the first precursor is
transformed to the lipid class via the first pathway, determining
P2, wherein P2 is the level of the marker composition in a second
precursor of the lipid class, wherein the second precursor is
transformed to the lipid class via the second pathway, determining
TL, wherein TL is the level of the marker composition in the lipid
class, wherein the contribution of the first pathway is represented
by (TL-P2)/(P1-P2) and the contribution of the second pathway is
represented by (TL-P1)/(P2-P1).
3. The method of claim 2, wherein the marker composition is a SN-1
position fatty acid.
4. The method of claim 2, wherein the marker composition is a fatty
acid selected from the group consisting of 16:0, 18:0, 18:1, 18:2,
20:4, and 22:6.
5. The method of claim 2, wherein the level of the marker
composition is represented by the level of 18:0 or 16:0.
6. The method of claim 2, wherein the level of the marker
composition is represented by the ratio of at least two fatty acids
at SN-1 position.
7. The method of claim 2, wherein the level of the marker
composition is represented by the ratio of 18:0 to 16:0.
8. The method of claim 2, wherein the level of the marker
composition is represented by the ratio of any two of 18:0, 16:0,
18:1, 18:2, 20:4, and 22:6.
9. The method of claim 2, wherein the level of the marker
composition is represented by the ratio of any three of 18:0, 16:0,
18:1, 18:2, 20:4, and 22:6.
10. The method of claim 2, wherein the lipid class is
phosphatidylcholine.
11. The method of claim 2, wherein the lipid class is
phosphatidylethanolamine, cholesterol ester, phosphatidylserine,
phosphatidylinositol, cardiolipin, triacylglyceride,
diacylglyceride, phosphatidic acid, free fatty acid, sphingomyelin,
phosphatidylglycerol, or lysophosphalipids.
12. The method of claim 2, wherein the lipid class is
phosphatidylcholine, the first pathway is
phosphatidylethanolamine-N-methyltransferase (PEMT) pathway, and
the second pathway is CDP-choline pathway.
13. The method of claim 2, wherein the lipid class is
phosphatidylcholine, the first pathway is
phosphatidylethanolamine-N-methyltransferase (PEMT) pathway and the
first precursor is phosphatidylethanolamine.
14. The method of claim 2, wherein the lipid class is
phosphatidylcholine, the second pathway is CDP-choline pathway and
the second precursor is selected from the group consisting of
diacylglyceride, phosphatidic acid, and triacylglyceride.
15. The method of claim 2, wherein the lipid class is
phosphatidylethanolamine, the first pathway is phosphatidylserine
decarboxylase pathway and the second pathway is CDP-ethanolamine
pathway.
16. The method of claim 2, wherein the lipid class is
phosphatidylethanolamine, the first pathway is phosphatidylserine
decarboxylase pathway and the first precursor is
phosphatidylserine.
17. The method of claim 2, wherein the lipid class is in
plasma.
18. The method of claim 2, wherein the lipid class is in liver.
19. The method of claim 2, wherein the lipid class is in brain,
heart, mammary gland, or intestine.
20. A method of determining the level of a marker composition of
phosphatidylcholine in liver comprising determining the level of
the marker composition of phosphatidylcholine in plasma.
Description
RELATED APPLICATIONS
[0001] The present application is a continuation of U.S.
application Ser. No. 10/615,966, filed Jul. 9, 2003, which is a
continuation of U.S. application Ser. No. 10/383,671, filed Mar. 7,
2003, which claims priority under 35 U.S.C. .sctn.119(e) from
provisional application Nos. 60/363,587, filed Mar. 11, 2002,
60/373,912, filed Apr. 19, 2002, 60/401,684, filed Aug. 6, 2002,
60/424,949, filed Nov. 8, 2002, and 60/436,192, filed Dec. 24,
2002. The disclosures of U.S. application Ser. No. 10/615,966,
filed Jul. 9, 2003, are hereby incorporated by reference herein in
their entirety.
FIELD OF THE INVENTION
[0002] This invention relates generally to the field of assessing
and monitoring metabolic processes, especially biosynthesis of
lipid metabolites.
BACKGROUND OF THE INVENTION
[0003] Metabolites are synthesized and regulated by various
metabolic processes and pathways. Each metabolite and its metabolic
pathways are inevitably involved in certain biological processes of
a system, e.g., human and could play an important role in a
system's function and regulation. Therefore, it is useful to
understand how metabolites, e.g., lipid metabolites are regulated
by their biosynthesis pathways. There is a great need in the field
to develop various ways to assess metabolic processes or pathways,
e.g., measure contributions of pathways to metabolite
productions.
SUMMARY OF THE INVENTION
[0004] The present invention is based, in part, on the discovery
that levels of metabolite precursors, for each pathway can be used
to determine each pathway's contribution to a metabolite
production. Accordingly, the present invention provides methods for
determining the contribution of a pathway to the biosynthesis of a
metabolite, e.g., lipid class and databases or metabolite profiles
generated therefrom.
[0005] In one embodiment, the present invention provides a method
for determining the contribution of a pathway to the biosynthesis
of a lipid class. The method includes determining the level of a
marker composition in a precursor, determining the level of the
marker composition in a lipid class, wherein the precursor is
transformed to the lipid class via a pathway, and wherein the level
of the marker composition in the precursor relative to the level of
the marker composition in the lipid class is indicative of the
contribution of the pathway to the biosynthesis of the lipid
class.
[0006] In another embodiment, the present invention provides a
method of determining the contribution of a first pathway and a
second pathway to the biosynthesis of a lipid class. The method
includes determining P1, wherein P1 is the level of a marker
composition in a first precursor of a lipid class, wherein the
first precursor is transformed to the lipid class via the first
pathway, determining P2, wherein P2 is the level of the marker
composition in a second precursor of the lipid class, wherein the
second precursor is transformed to the lipid class via the second
pathway, determining TL, wherein TL is the level of the marker
composition in the lipid class, wherein the contribution of the
first pathway is represented by (TL-P2)/(P1-P2) and the
contribution of the second pathway is represented by
(TL-P1)/(P2-P1).
[0007] In yet another embodiment, the present invention provides a
method of providing a service. The method includes providing a
signal identifying the contribution of a pathway to the
biosynthesis of a lipid class in a sample as determined by the
method provided by the present invention.
[0008] In still another embodiment, the present invention provides
a method of providing a service. The method includes providing a
signal identifying the contribution of a first pathway or second
pathway or both to the biosynthesis of a lipid class in a sample as
determined by the method provided by the present invention.
[0009] In another embodiment, the present invention provides a
database which includes one or more signals, wherein each signal
identifies the contribution of a pathway to the biosynthesis of a
lipid class in a sample as determined by the method provided by the
present invention.
[0010] In yet another embodiment, the present invention provides a
database which includes one or more signals; wherein each signal
identifies the contribution of a first pathway or a second pathway
or both to the biosynthesis of a lipid class in a sample as
determined by the method provided by the present invention.
[0011] In another embodiment, the present invention provides a
method of providing a service. The method includes analyzing the
database of the present invention and providing a signal
identifying a profile corresponding to a characteristic of a sample
in the database, wherein the profile comprises the contribution of
at least one pathway to at least one lipid class.
[0012] In another embodiment, the present invention provides a
method of determining the level of a marker composition of
phosphatidylcholine in liver. The method includes determining the
level of the marker composition of phosphatidylcholine in
plasma.
[0013] In yet another embodiment, the present invention provides a
method of determining the activity of
phosphatidylethanolamine-N-methyltransferase (PEMT) pathway in a
system. The method includes determining the level of 20:4n6 or
22:6n3 in the system.
[0014] In another embodiment, the present invention provides a
method of identifying a diagnostic marker for a condition. The
method includes determining the contribution of a pathway to the
biosynthesis of a lipid class according to the method provided by
the present invention in a sample from normal condition and a
sample from said condition, wherein a variation in the contribution
of the pathway associated with the sample from said condition, but
not associated with the sample from the normal condition is
indicative that the contribution of the pathway to the biosynthesis
of the lipid class is a diagnostic marker for said condition.
[0015] In yet another embodiment, the present invention provides a
method for determining the contribution of Acyl-CoA:cholesterol
acyltransferase (ACAT) to the biosynthesis of cholesterol ester in
plasma. The method includes determining a relative level, wherein
the relative level is the level of a saturated fatty acid in
cholesterol ester from plasma relative to the level of the
saturated fatty acid in cholesterol ester from liver and wherein
the relative level is indicative of the contribution of ACAT to the
biosynthesis of cholesterol ester in plasma.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0016] The present invention is based, in part, on the discovery
that levels of metabolite precursors for each biosynthesis pathway
can be used to determine each pathway's contribution to a
metabolite production.
[0017] According to the present invention, one can choose a marker
composition to track a desired metabolite precursor's contribution
to a product's biosynthesis or track the pathway or enzyme activity
transforming the desired metabolite precursor to a product. For
example, the level of a marker composition in a precursor relative
to the level of the marker composition in the product associated
with the precursor is indicative of the contribution of the pathway
or pathway activity converting the precursor to the product.
[0018] A marker composition can be any composition that is uniquely
or characteristically associated with a pathway or enzyme activity
or is stable and relatively unchanged throughout the biosynthesis
of a product. In one embodiment, a marker composition can be one or
more fatty acids, e.g., saturated fatty acids at SN-1 position of a
metabolite, e.g., lipid class. For example, the marker composition
can be 18:0 or 16:0 at SN-1 position of a fatty acid. In another
embodiment, a marker composition can be one or more fatty acids at
SN-1 or SN-2 position of a lipid class that are stable and
relatively unchanged from the precursor stage to the product stage.
Examples of such fatty acid include, without any limitation, 16:0,
18:0, 18:1, 18:2, 20:4 (20:4n6), and 22:6 (22:6n3).
[0019] In yet another embodiment, a marker composition can be one
or more fatty acids that are characteristically or uniquely
associated with a particular pathway for a precursor, but not
significantly associated with other pathways for other precursors
of the product. For example, 16:0 is particularly enriched in the
precursor of CDP-choline pathway for the biosynthesis of
phosphatidylcholine (PC) while 18:0, 22:6n3, and 20:4n6 are
particularly enriched in the precursor of the
phosphatidylethanolamine-N-methyltransferase (PEMT) pathway for the
biosynthesis of PC.
[0020] Saturated fatty acids and monounsaturated fatty acids, e.g.,
16:0, 16:1n7, and 18:0 are esterified to cholesterol by
Acyl-CoA:cholesterol acyltransferase (ACAT) while polyunsaturated
fatty acids, e.g., 20:4n6, 20:5n3, and 22:6n3 are esterified to
cholesterol by lecithin:cholesterol acyltransferase (LCAT). In
addition, 18:0, 22:6n3, and 20:4n6 are characteristically
associated with the precursors of phosphatidylserine decarboxylase
pathway for the biosynthesis of phosphatidylethanolamine (PE) while
16:0, 18:1, and 18:2n6 are characteristically associated with the
precursors of CDP-ethanolamine pathway for the biosynthesis of
PE.
[0021] In still another embodiment, a marker composition of 18:0,
16:0, or the ratio of 18:0 to 16:0 is used for the biosynthesis of
PC, PE, diacylglyceride, triacylglyceride, 1,acyl-monoacylglyceride
3,phosphate, cholesterol ester, phosphatidic acid, cardiolipin,
phosphatidylinositol, phosphatidylserine, and lysophospholipid.
[0022] The level of a marker composition usually can be the
concentration of the marker composition, the level of the marker
composition normalized against its corresponding class, e.g., total
fatty acids, or the ratio of two or more fatty acids within the
marker composition. For example, the level of a marker composition
can be the level of 16:0, 18:0, 18:1, 18:2, 20:4n6, or 22:6n3
normalized against the total amount of fatty acids in the class.
Alternatively the level of a marker composition can be represented
by the ratio of any two, three, four, five, or six of 16:0, 18:0,
18:1, 18:2, 20:4n6, and 22:6n3.
[0023] In one embodiment, the level of a marker composition is the
level of 18:0 or 16:0. In another embodiment, the level of a marker
composition is the ratio of 18:0 to 16:0. In yet another
embodiment, the level of a marker composition is the level of 18:1,
18:2, 20:4, or 22:6. In still another embodiment, the level of a
marker composition is the ratio of any two, three, or four of 18:1,
18:2, 20:4 and 22:6.
[0024] The level of a marker composition can be determined by any
suitable means. For example, the level of a marker composition for
a precursor or a product can be determined by gas chromatography,
high performance chromatography nuclear magnetic resonance, mass
spectrometry, immunoassay, thin-layer chromatography, etc.
[0025] According to the present invention, the level of a marker
composition in a precursor relative to the level of the marker
composition in a product associated with the precursor can be used
to assess the biosynthesis of a variety of metabolites, e.g.,
lipids. Examples of various pathways whose contribution to the
biosynthesis of a metabolite can be monitored or measured using
such relative level includes, without any limitation,
phosphatidylethanolamone-N-methyltransferase (PEMT) pathway,
CDP-choline pathway, phosphatidylserine decarboxylase (PSDC)
pathway, CDP-ethanolamine pathway, diacylglyceride acyltransferase
(DGAT) pathway, monoacylglyceride acyltransferase (MGAT) pathway,
glycerolphosphate acyltransferase (GPAT) pathway,
Acyl-CoA:cholesterol acyltransferase (ACAT) pathway, lecithin:
cholesterol acyltransferase (LCAT) pathway, phospholipase C
pathway, phospholipase D pathway, lipoprotein lipase,
hormone-sensitive lipase, hepatic lipase and other lipases,
cardiolipin synthase, phosphatidylinositol synthase,
phosphatidylserine synthase, and phospholipase A2.
[0026] Examples of various lipid classes whose biosynthesis can be
analyzed using such relative level include, without any limitation,
phosphatidylcholine, phosphatidylethanolamine, cholesterol ester,
phosphatidylserine, phosphatidylinositol, cardiolipin,
triacylglyceride, diacylglyceride, phosphatidic acid, free fatty
acid, sphingomyelin, phosphatidylglycerol, lysophospholipid, and
1,acyl-monoacylglyceride 3,phosphate.
[0027] In one embodiment, the level of a marker composition in a
precursor relative to the level of the marker composition in a
product associated with the precursor can be used to assess
pathways or activities substantially associated with a particular
marker composition in a product. For example, with respect to
phosphatidylcholine production, most of 18:0, 20:4n6, and 22:6n3
are derived from PEMT pathway while most of 16:0 is derived from
CDP-choline pathway. With respect to cholesterol ester production,
most of saturated and monounsaturated fatty acids, e.g., 16:0,
16:1n7, and 18:0 are derived from ACAT pathway while most
polyunsaturated fatty acids, e.g., 20:4n6, 20:5n3, and 22:6n3 are
derived from LCAT pathway. In addition, with respect to
phosphatidylethanolamine production, most of 16:0, 18:1 n9, and
18:2n6 are derived from the CDP-choline pathway while most of 18:0,
20:4n6, and 22:6n3 are derived from the phosphatidylserine
decarboxylase activity.
[0028] In another embodiment, the level of a marker composition in
a precursor relative to the level of the marker composition in a
product associated with the precursor can be used to assess the
contribution of PEMT pathway to the biosynthesis of
phosphatidylcholine, the contribution of CDP-choline pathway to the
biosynthesis of phosphatidylcholine, the contribution of PSDC
pathway to the biosynthesis of phosphatidylethanolamine, the
contribution of CDP-ethanolamine pathway to the biosynthesis of
phosphatidylethanolamine, the contribution of ACAT pathway to the
biosynthesis of cholesterol ester, the contribution of LCAT pathway
to the biosynthesis of cholesterol ester, the contribution of DGAT
pathway to the biosynthesis of diacylglyceride, the contribution of
MGAT pathway to the biosynthesis of diacylglyceride, the
contribution of GPAT pathway to the biosynthesis of
1,acyl-monoacylglyceride 3,phosphate, the contribution of
phospholipase C or D pathway to the biosynthesis of phosphotidic
acid, the contribution of lipoprotein lipase, hormone-sensitive
lipase, hepatic lipase, or any other lipase pathway to the
biosynthesis of diacylglyceride, the contribution of cardiolipin
synthase to the biosynthesis of cardiolipin, the contribution of
phosphatidylinosital synthase to the biosynthesis of
phosphatidylinositol, the contribution of phosphatidylserine
synthase to the biosynthesis of phosphatidylserine, and the
contribution of phospholipase A2 to the biosynthesis of
lysophospholipid.
[0029] In general, for the biosynthesis of phosphatidylcholine the
marker composition of the precursor for the PEMT pathway can be the
marker composition of phosphatidylethanolamine while the marker
composition of the precursor for the CDP-choline pathway can be the
marker composition of diacylglycerid, phosphatidic acid, or
triacylglyceride. With respect to the biosynthesis of
phosphatidylethanolamine, usually the marker composition of the
precursor for the PSDC pathway can be the marker composition of
phosphatidylserine while the marker composition of the precursor
for the CDP-ethanolamine pathway can be the marker composition of
1,2-diacylglyceride, triacylglyceride, or phosphatidic acid.
[0030] With respect to the biosynthesis of cholesterol ester, the
precursors for LCAT usually are fatty acids on the SN-2 position of
plasma phospholipids and for ACAT usually are fatty acid CoA esters
in liver. For example, saturated and monosaturated fatty acids such
as 16:0, 16:1n7, and 18:0 are usually precursors for ACAT while
polyunsaturated fatty acids such as 20:4n6, 20:5n3, and 20:6n3 are
usually precursors for LCAT; and 18:2n6 serves as a precursor for
both the ACAT and LCAT pathways. In one embodiment, the ACAT
pathway activity can be represented by the biosynthesis of
cholesterol ester in liver while the LCAT pathway activity can be
represented by the difference between the plasma and liver
cholesterol ester marker composition.
[0031] According to another aspect of the invention, the
contribution of a pathway to the biosynthesis of a product can also
be assessed by determining the product level and the precursor
levels of two or more pathways involved in the biosynthesis of the
same product. For example for a lipid biosynthesis comprising two
pathways, one can determine the contribution of each pathway by
determining the level of a marker composition in the precursor used
by the first pathway (P1), the level of the marker composition in
the precursor used by the second pathway (P2), and the level of the
marker composition in the lipid class (TL). The contribution of
each pathway can be determined by mathematical equations according
to the general principal that marker compositions in precursors are
relatively stable and unmodified during the biosynthesis of the
product from the precursors.
[0032] For example, in a biosynthesis comprising two pathways, the
contribution of the first pathway (C1) can be represented by
(TL-P2)/(P1-P2) while the contribution of the second pathway (C2)
can be represented by (TL-P1)/(P2-P1), both of which are obtained
based on equations I and II as the following: C1+C2=1 (I)
C1.times.P1+C2.times.P2=TL (II).
[0033] Usually, when the biosynthesis of a product contains more
than two pathways, more than one marker composition could be used
and the contribution of each pathway can be readily obtained
according to the general principals described by equations I and
II. In general, the equations provided by the present invention
representing the contributions of two or more pathways can be
further modified by a constant or conversion factor.
[0034] In one embodiment, the product is phosphatidylcholine, the
first pathway is PEMT pathway using phosphatidylethanolamine as
precursor, and the second pathway is CDP-choline pathway using
diacylglyceride, phosphatidic acid, or triacylglyceride as
precursor. In another embodiment, the product is
phosphatidylethanolamine, the first pathway is PSDC using
phosphatidylserine as precursor, and the second pathway is
CDP-ethanolamine pathway using 1,2-diacylglyceride,
triacylglycerid, or phosphatidic acid as precursor.
[0035] The contributions of various pathways as determined by the
methods provided by the present invention can be relative
contributions or quantified contributions. For example, the
contribution of a pathway, e.g., PEMT to the biosynthesis of a
lipid, e.g., phosphatidylcholine can be a percentage contribution
or a contribution in quantitative amount, e.g. determined by the
percentage contribution and the concentration of the lipid
class.
[0036] The methods provided by the present invention for measuring
the contribution of a pathway to the biosynthesis of a metabolite
can be used to assess metabolite production in various conditions
and from various sources. For example, the methods provided by the
present invention can be used to analyze the biosynthesis of
metabolites, e.g., lipids in vivo or in vitro. In one embodiment,
the methods provided by the present invention can be used to
analyze the lipids in various tissues including, without any
limitation, liver, brain, heart, mammary gland, intestine, plasma,
kidney, and pancreas.
[0037] According to one embodiment of the present invention, the
level of a marker composition for phosphatidylcholine,
triacylglyceride, or phophatidylethanolamine in plasma is
representative of the level of a marker composition for
phosphatidylcholine, triacylglyceride, or phosphatidylethanolamine
in liver, respectively. In another embodiment of the present
invention, the level of 20:4n6 or 22:6n3, e.g., in plasma is
representative of the level of PEMT pathway activity, e.g., in
liver.
[0038] According to another embodiment of the present invention,
the level of a marker fatty acid in cholesterol ester in plasma
relative to the level of the marker fatty acid in cholesterol ester
in liver is representative of the contribution of
Acyl-CoA:cholesterol acyltransferase (ACAT) to the biosynthesis of
cholesterol ester in plasma. A marker fatty acid can be any fatty
acid that are substantially the substrate for ACAT, but not LCAT.
For example, most saturated fatty acids or monounsaturated fatty
acids are substrates for ACAT while most polyunsaturated fatty
acids are substrates for LCAT. In one embodiment, the concentration
of a saturated fatty acid, e.g., 16:0 in cholesterol ester in
plasma and liver is used to determine the percentage contribution
of ACAT, and thus LCAT to the total cholesterol ester concentration
of plasma.
[0039] According to the present invention, the composition of
cholesterol ester in liver is derived substantially from ACAT
pathway and the total composition of cholesterol ester in plasma is
the sum total of cholesterol ester produced via ACAT pathway and
exported to plasma and cholesterol ester produced via LCAT in
plasma. Therefore, the contribution of ACAT pathway can be
determined by determining the dilution of the marker fatty acid of
the present invention in the plasma cholesterol ester whereas the
contribution of LCAT pathway corresponds to the sum total of
cholesterol ester produced excluding the contribution of ACAT
pathway.
[0040] According to the present invention, methods for analyzing
the biosynthesis of a metabolite as provided by the present
invention have various applications in areas such as
bioinformatics, therapeutics or diagnostics. In one embodiment,
methods provided by the present invention can be used to provide
services to an entity. For example, one can receive samples from a
requesting party or obtain samples designated by a requesting
party, analyze the contribution of one or more pathways to one or
more metabolites in these samples according to the methods provided
by the present invention, and provide the relevant results back to
the requesting party, e.g., as electronic signals or computer
readable form via any suitable means, e.g., internet, intranet, or
wireless connection. Optionally one can provide an analysis of the
results for the requesting party, e.g., searching the result
database to identify any correlation between a characteristic of a
sample, e.g., an abnormal or testing condition of a sample and the
contribution pattern of one or more pathways to one or more
metabolites.
[0041] In another embodiment, methods provided by the present
invention can be used to build a database containing information of
biosynthesis analyses, e.g., contribution of one or more pathways
to one or more metabolites as part or all of the metabolic profile
for a subject, e.g., human.
[0042] Usually the database provides one or more signals, outputs,
or data points, each of which identifying contribution of a pathway
to a metabolite corresponding to a subject under a condition. The
subject can be any biosystem including, without any limitation,
animals, humans, etc. or the samples thereof. The condition can be
any suitable condition, e.g., one or more abnormal conditions,
treatment of one or more therapeutic agent or testing agents,
dietary conditions, various physiological conditions, etc. The
database can be in any form that is accessible to a user. For
example, the database can be in a computer readable form or
accessible by a remote location or a predetermined entity, e.g.,
via internet, intranet, or wireless connection. In one embodiment,
the database is searchable for any correlation between one or more
pre-determined conditions, e.g., a subject with a disease condition
and the contribution pattern of one or more pathways to one or more
metabolite productions.
[0043] In yet another embodiment, the methods provided by the
present invention can be used to identify targets for therapeutic
treatments or markers for diagnostics. Any contribution pattern of
one or more pathways that is associated with an abnormal condition,
but not with a normal condition, can be used at a diagnostic marker
for the abnormal condition and/or a target for the treatment of the
abnormal condition.
[0044] For example, one can identify a diagnostic marker by
comparing the contribution pattern of a pathway between a normal
condition and a known abnormal condition, e.g., a known disease or
sub-optimal condition and identify contribution patterns that are
hallmarks for the known abnormal condition, thus identify
diagnostic markers for the known abnormal condition. In one
embodiment, one can determine the contribution of one or more
pathways to the biosynthesis of one or more lipid classes according
to the methods provided by the present invention in a sample from
normal condition and a sample from a known abnormal condition. Any
variation in the contribution of the pathways that is significantly
associated with the known abnormal condition, but not with the
normal condition is indicative that the varied contribution pattern
of the pathways can be used as a diagnostic marker for the known
abnormal condition, e.g., a testing subject having the varied
contribution pattern of the pathways is having the known abnormal
condition.
EXAMPLES
[0045] The following examples are intended to illustrate but not to
limit the invention in any manner, shape, or form, either
explicitly or implicitly. While they are typical of those that
might be used, other procedures, methodologies, or techniques known
to those skilled in the art may alternatively be used.
[0046] Symbols used in the examples: [0047] IV: Liver [0048] PLA:
Plasma [0049] ADP: Adipose [0050] HRT: Heart [0051] MUS: Muscle
[0052] PC: Phosphatidylcholine [0053] PE: Phosphatidylethanolamine
[0054] PS: Phosphatidylserine [0055] PA: Phosphatidic Acid [0056]
TG: Triacylglyceride [0057] CE: Cholesterol Ester [0058] FS: Free
Sterol [0059] DG: 1,2-Diacylglyceride [0060] FA: Free Fatty Acid
[0061] SP: Sphingomyelin [0062] CL: Cardiolipin Hence, the symbol
LIVPC16:0 denotes the concentration of 16:0 in liver
phosphatidylcholine (expressed in nMoles per g). The symbol %
LIVPC16:0 indicates the mole percentage concentration of 16:0 in
liver phosphatidylcholine (expressed as a percentage of the total
amount of fatty acids in liver phosphatidylcholine).
[0063] The composition of each lipid class is highly regulated, and
changes in the concentration of certain fatty acids within a lipid
class can be used to determine which pathway is responsible for the
production of that lipid class. The primary mathematical approach
used herein is a solver equation, whereby the concentration of a
given fatty acid within the two or more precursor lipid classes,
and the concentration of that fatty acid in the product lipid
class, are used to estimate the relative flux through the two
enzyme systems that modify substrate into product.
[0064] Other approaches can be used, some of these may resemble
regression analyses or other statistical techniques. The absolute
concentration of the product lipid class can be used to estimate
the steady state contribution of each contributing metabolic
pathway to the concentration in the product lipid class.
[0065] The solver or regression approach described herein relies on
using accurate substrate and/or product composition data to
calculate the flux of the enzyme pathway(s) contributing to the
measured class(es). Ideally, the quantitative concentration of each
lipid class can be used to scale the assay to calculate the
absolute concentration or amount of the lipid class synthesized via
a given pathway. A solver approach takes (1) the concentration of a
fatty acid in each of the two (or more, if there are more pathways
present) possible precursors and (2) the concentration of that same
fatty acid in the product, and (3) determines the percent
contribution of each of the two pathways to the production of that
product.
Example 1
Analysis of Phosphatidylcholine Production
[0066] Phosphatidylcholine is primarily synthesized via one of two
pathways, the PEMT pathway and the CDP-choline pathway. The
CDP-choline pathway synthesizes phosphatidylcholine from
diacylglyceride and phosphocholine, and the PEMT pathway
synthesizes phosphatidylcholine from phosphatidylethanolamine and
S-adenosylmethionine. (Reo et al., Biochim Biophys Acta
1580(23):171-188, 2002).
[0067] The relative contribution of each of these pathways to total
liver phosphatidylcholine composition has been estimated by several
groups. Reo et al. (2002) using radiolabeled choline and
ethanolamine has determined that in rats approximately 70 percent
of hepatic phosphatidylcholine was synthesized by the CDP-choline
pathway and 30 percent was synthesized by the PEMT pathway. These
results were generally in agreement with previous findings
(references 4, 16-19 in Reo et al., 2002). Roy et al. (2002)
additionally demonstrated that newly synthesized
phosphatidylethanolamine is preferentially used for the PEMT
reaction (the current solver approach may not provide true 0 and
unity endpoints because of this phenomenon).
[0068] Kinetic analysis showed conversion of
phosphatidylethanolamine to phosphatidylcholine occurred at three
times the rate of diacylglyceride to phosphatidylcholine via the
CDP-choline pathway (Reo et al., 2002). The CDP-choline pathway
activity is dependent on choline status and the CDP-ethanolamine
pathway is dependent on ethanolamine status. Therefore, it is
possible to modulate both pathways via their respective substrate.
The activation of these pathways takes place at the kinase step.
Since choline kinase and ethanolamine kinase may be in fact the
same enzyme, it is possible that choline and ethanolamine act as
competitive inhibitors for the other pathway.
[0069] In the inventor's experience, phosphatidylethanolamine
concentrations are usually found to be constant at around 8-10,000
nanomoles per gram in mouse liver, thus, it is believed that
phosphatidylethanolamine synthesis and conversion to other
glycerolipid classes is highly regulated. The metabolic mechanisms
by which phosphatidylethanolamine concentrations can be maintained
include it's biosynthesis via phosphatidylserine decarboxylase and
CDP-ethanolamine pathways, and its degradation or conversion to
other glycerolipid classes by PEMT or phospholipase activity.
[0070] The PEMT gene gives rise to two enzymatic isoforms, PEMT1
and PEMT2. PEMT1 activity is present in the endoplastic reticulum
and is likely the isoform involved in lipoprotein export and PEMT2
activity is found in the mitochondria. There are some data to
suggest that the second form of PEMT is involved in cell
proliferation and potentially cancer (see, e.g., Tessitore et al.,
Carcinogenesis 20(4):561-567, 1999).
[0071] The fatty acid composition of phosphatidylcholine produced
via the CDP-choline pathway in the PEMT pathway has been studied by
DeLong et al. (J Biol Chem. 274(42):29683-29688, 1999).
Phosphatidylcholine species produced via the CDP-choline pathway
"were mainly comprised of median chain, saturated (e.g., 16:0/18:0)
species. On the other hand, PC molecules from the PE methylation
pathway contain a higher percentage of arachidonic and were more
diverse than those from the CDP: choline pathway."
[0072] An analysis of the data from the DeLong et al. (1999) paper
show that 16:0, 18:2, 18:1 and 20:4 are the predominant fatty acids
of phosphatidylcholine produced via the CDP-choline pathway. In
contrast, 18:0, 20:4, 16:0, 18:1, and 18:2 were the predominant
fatty acids produced via the PEMT pathway. The inventor believes
that 20:4 could play an important role in intercellular signaling
and PEMT could have a role in generating lipids active in cellular
regulation. The authors of DeLong et al. do not identify 22:6 as a
hallmark fatty acid of PEMT activity, despite its presence in
phosphatidylcholine (although in low concentrations) in this
study.
[0073] It is the discovery of the present invention that 18:0,
20:4, and 22:6 are hallmark fatty acids of phosphatidylcholine
produced via the PEMT pathway, while 16:0, 18:1, and 18:2 are
hallmark fatty acids of the CDP-choline pathway. While it is useful
for many assays to have a marker for one of the two pathways that
is unique, the solver approach described herein utilizes the
composition of the precursors to phosphatidylcholine to determine
the relative flux through each of two main phosphatidylcholine
biosynthesis pathways.
[0074] In particular, this analysis takes advantage of the fact
that it is reasonable to assume that the 16:0 and 18:0 present in
phosphatidylcholine is on the SN-1 position, and that this position
is stable and not remodeled by phospholipase after the conversion
of phosphatidylethanolamine and diacylglyceride to
phosphatidylcholine. Thus, by knowing the composition of the SN-1
position of phosphatidylcholine and its precursors, the percent
contribution of each of the two precursors to phosphatidylcholine
concentrations can be calculated using the methods described
herein.
[0075] Because phosphatidylcholine is synthesized by the
modification of the head groups of 1,2-diacylglyceride (1,2-DAG) or
phosphatidylethanolamine (PE) by the CDP-choline or PEMT pathways,
respectively (meaning the fatty acid composition of these
precursors is not altered by the reactions themselves), and because
1,2-DAG and PE have unique fatty acid compositions, the proportion
of PC synthesized from either 1,2-DAG or PE can be calculated from
the fatty acid composition of the precursors and PC.
[0076] In particular, the saturated fatty acid composition of PC
and its precursors is thought to be useful because of a relatively
constant biological property of phospholipids. Phospholipids
contain almost exclusively saturated fatty acids at the SN-1
position (the first of their two hydroxyl groups available for
fatty acid esterification), thus, the composition of phospholipids
is approximately 50% saturated (it's typically close to 46%).
Although the SN-1 position contains almost entirely saturated fatty
acids, the chain length of the saturated fatty acid can vary, and
each lipid class typically has a unique "standard" composition. The
following table displays the means and standard deviations for the
16:0, 18:0 and total saturated fatty acid composition of the major
liver lipids in mice: TABLE-US-00001 % Other Lipid Class Saturated
%16:0 %18:0 Saturates Phosphatidylcholine 45.8 .+-. 1.7 33.4 .+-.
3.4 11.7 .+-. 2.9 0.7 .+-. 0.4 (PC) Phosphatidyletha- 40.6 .+-. 2.1
21.9 .+-. 1.6 18.1 .+-. 2.4 0.6 .+-. 0.3 nolamine (PE)
Phosphatidylserine 47.3 .+-. 3.8 9.0 .+-. 1.9 37.0 .+-. 4.7 1.3
.+-. 0.7 (PS) Diacylcglyceride (DG) 32.1 .+-. 5.5* 23.6 .+-. 4.1
5.3 .+-. 1.7 3.2 .+-. 1.0 Triacylglyceride (TG) 30.8 .+-. 4.7* 27.0
.+-. 4.6 2.2 .+-. 0.9 1.6 .+-. 0.5 *See below for why these lipids
are comprised of less saturated fatty acids than their phospholipid
analogues.
Using Fatty Acid Composition to Estimate Proportional Contribution
of PEMT to Total PC Biosynthesis.
[0077] The 18:0 and 16:0 composition of phosphatidylcholine is
indicative of the pathway from which phosphatidylcholine is
synthesized. Generally, phosphatidylcholine with 16:0 in the SN-1
position is derived from the CDP-choline pathway and
phosphatidylcholine with 18:0 in the SN-1 position is derived from
the PEMT to pathway. Therefore the contribution from PEMT or
CDP-choline pathway can be calculated based on the level of 16:0
and 18:0 in the precursors and the level of
phosphatidylcholine.
[0078] To be more precise, the exact composition of diacylglyceride
phosphatidylethanolamine, and phosphatidylcholine in a tissue can
be used to calculate the relative flux of the PEMT and CDP-choline
pathways. Specifically, the ratio of 18:0 to 16:0 in each of the
precursors was determined and used to "solve" for the ratio of 18:0
to 16:0 in the PC product.
[0079] In general, one could 1) determine the fatty acid
composition of phosphatidic acid or diacylglyceride,
phosphatidylcholine, and phosphatidylethanolamine in liver, and 2)
use the composition of the precursors of each of the two
biosynthetic pathways and phosphatidylcholine to determine the
relative contribution of each biosynthetic pathway to total
phosphatidylcholine concentrations.
[0080] The calculation can be carried out as the following.
[0081] Values: [0082] k1: percentage of PE going into PC [0083] k2:
percentage of PA going into PC [0084] val_pe: PE (X)measured [0085]
val_pa; val_dag: PA or 1,2-DAG(X)measured [0086] val_pc: PC
(X)measured where X equals the concentration of 16:0 or 18:0 within
the appropriate lipid class expressed as a percentage of total
fatty acids within that class or is the ratio of the concentrations
of 18:0 to 16:0 within the lipid class.
[0087] Constraints: Set k1+k2=1
(k1*val.sub.--pe)+(k2*val.sub.--pa)=val.sub.--pc
[0088] Results: [0089] k1=Percentage contribution of PEMT pathway.
[0090] k2=Percentage contribution of CDP-choline pathway
[0091] The following table is a screen capture of the Excel
Datasheet used to calculate the percentage contribution of PEMT and
CDP-choline to the synthesis of PC. Phosphatidic acid was used as a
surrogate for 1,2-DAG, the precursor of the CDP-choline pathway. PA
composition was calculated from the composition of TAG as described
below. The table at the bottom right is the input box into which
data from a sample is pasted. ##STR1##
[0092] Several issues should be considered in calculating the
activity of PEMT or CDP-choline pathway activity by using the
composition of 1,2-DAG as the precursor for the CDP-choline
pathway. First, the composition of 1,2-DAG, the direct precursor of
PC via the CDP-choline reaction, is not always reflective of the PC
precursor pool, because 1,2-DAG can be synthesized via two
different pathways, with the second (non phosphatidic acid-derived)
pathway often producing the majority of the 1,2-DAG. Therefore, the
composition of phosphatidic acid can act as a surrogate for the
appropriate 1,2-DAG, because it can be assumed to be the direct and
only precursor to 1,2-DAG that will be converted to PC. A simple
measurement of phosphatidic acid fatty acid composition will
provide the appropriate data for the assay.
[0093] In addition, the composition of phosphatidic acid (PA)
should be exactly reflective of the 1,2-DAG substrate available for
conversion to PC, but the composition of PA could be difficult to
measure at times. Therefore, the saturated fatty acid composition
of TAG can act as a surrogate for the saturated fatty acid
composition of PA because it's saturated fatty acids are in the
SN-1 position and derived from the saturated fatty acids of PA.
However, because TAG contains 3 fatty acids, rather than 2, and
because the fatty acid that can be cleaved off to form 1,2-DAG is
ostensibly random, the total content of saturated fatty acids must
be normalized to .about.45%, the putative content of phosphatidic
acid.
[0094] For example, using TAG as a surrogate for PA, the
calculation can be carried out as the following.
[0095] 1. Calculating the composition of phosphatidic acid
(PA):
Total saturated fatty acid composition of PA=0.45.sup.1
Percentage of PA comprised by: 16:0=(TAG % 16:0*0.45.sup.1)/TAG
%.sub.Total Saturated FA Composition Percentage of PA comprised by:
18:0=(TAG % 18:0*0.45.sup.1)/TAG %.sub.Total Saturated FA
Composition Ratio of 18:0 to 16:0 in PA is calculated from the
above estimated values.
[0096] 2. Solver Equation:
[0097] Values: .sup.1 The value 0.45 was chosen because it is
typically the percent of total fatty acids comprised by saturates
within phosphatidic acid. A number appropriate for the biological
system under investigation should be used here. [0098] k1:
percentage of PE going into PC [0099] k2: percentage of PA going
into PC [0100] val_pe: PE (ratio of 18:0 to 16:0).sub.measured
[0101] val_pa: PA (ratio of 18:0 to 16:0).sub.estimated from TAG
[0102] val_pc: PC (ratio of 18:0 to 16:0).sub.measured
[0103] Constraints: Set k1+k2=1
(k1*val.sub.--pe)+(k2*val.sub.--pa)=val.sub.--pc
[0104] Results: [0105] k1=Percentage contribution of PEMT pathway
[0106] k2=Percentage contribution of CDP-choline pathway
[0107] The following table is a screen capture of the Excel
Datasheet used to calculate the percentage contribution of PEMT and
CDP-choline to the synthesis of PC. Phosphatidic acid was used as a
surrogate for 1,2-DAG, the precursor of the CDP-choline pathway. PA
composition was calculated from the composition of TAG as described
above. The table at the bottom right is the input box into which
data from a sample is pasted. ##STR2## Using Other Fatty Acids to
Calculate Pathway Flux or to Estimate the Degree of
Phosphatidylcholine Remodeling.
[0108] Using 16:0, 18:0 or the ratio 18:0 to 16:0 within each of
the substrate and product lipid class to calculate pathway flux
provides the most stable assay because these fatty acids are
present at the SN-1 position of the phospholipids, and are not
actively hydrolyzed by phospholipases.
[0109] Other fatty acids within phosphatidylcholine,
diacylglycerides, and phosphatidylethanolamine can be plugged into
these equations as well, even though these other fatty acids are
present at the SN-2-position, which is more actively hydrolyzed by
phospholipases in the process of remodeling. Thus, the degree of
remodeling within phosphatidylcholine after its conversion from
diacylglyceride or phosphatidylethanolamine can be calculated by
comparing the unsaturated fatty acid composition of
phosphatidylcholine with its precursors. Because the present method
calculates the percentage contribution of each pathway to the total
amount of phosphatidylcholine, the difference between the
concentration of unsaturated fatty acids within phosphatidylcholine
as measured, and as it is predicted by and the mixing of these two
substrate pools can be assumed to be the degree of SN-2 position
remodeling of phosphatidylcholine.
PEMT Assay in Liver
[0110] The following assay calculates the percentage of total liver
phosphatidylcholine produced by PEMT. x=(((% LIVPC(y))-(%
LIVDG(y)))/(((% LIVPE(y))-(% LIVDG(y))) Where: x=the percentage of
total liver phosphatidylcholine produced by PEMT and: (y)=16:0,
18:0 or a ratio of the two.
[0111] In many cases, the liver DG may not be an acceptable
component of this equation. For instance, if the majority of the DG
in liver is produced by hydrolysis of triacylglyceride or
phospholipid rather than by the hydrolysis of phosphatidic acid (de
novo synthesis of 1,2-DG occurs by conversion of phosphatidic
acid), then a surrogate for de novo synthesized DG should be used.
Good surrogates include phosphatidic acid and triacylglycerides. If
triacylglycerides are used in place of diacylglycerides in this
equation, then the final mole percentage concentration of the
metabolite (i.e. TG16:0) should be divided by 0.66 because
diacylglycerides have 2/3rds the number of fatty acids per molecule
as do triacylglycerides.
Equations using surrogates for 1,2-DG include: x=((% LIVPC(y))-(%
LIVPA(y)))/(((% LIVPE(y))-(% LIVPA(y))) x=((% LIVPC(y))-((%
LIVTG(y))/0.66))/(((% LIVPE(y))-(% LIVTG(y))/0.66)) Where: x=the
percentage of total liver phosphatidylcholine produced by PEMT and:
(y)=16:0, 18:0 or the ratio of the two.
[0112] Because phosphatidylcholine is synthesized by either the
PEMT pathway or the CDP-choline, the percentage of liver
phosphatidylcholine produced by the CDP-choline pathway can be
calculated from the percentage of phosphatidylcholine produced by
PEMT.
Percentage of liver phosphatidylcholine produced by the CDP-choline
pathway: z=1-x Where z=the percentage of liver phosphatidylcholine
produced by the CDP-choline pathway And: x=the percentage of liver
phosphatidylcholine produced by the PEMT pathway
[0113] The quantitative amount of phosphatidylcholine produced by
each pathway can be calculated from these calculated values and the
quantitative amount of phosphatidylcholine in the liver.
Quantitative amount of liver phosphatidylcholine produced by:
PEMT=x (see above)*LIVPCtot_nmoles_per_g CDP-Choline=z (see
above)*LIVPCtot_nmoles_per_g
[0114] The quantitative amount of PC produced by each pathway in
tissues other than liver can be calculated in the same way.
[0115] The quantitative amount of PC produced by each pathway in
plasma can be calculated in the same way.
Example 2
Analysis of Phosphatidylserine Decarboxylase/CDP-Ethanolamine
Pathways
[0116] Synopsis of Assay: The same assay protocol as described for
the PEMT protocol can be used to determine the contribution of the
phosphatidylserine decarboxylase and CDP-ethanolamine pathways to
the biosynthesis of phosphatidylethanolamine. The 18:0 content of
phosphatidylethanolamine is principally derived from
phosphatidylcholine and 16:0 content of phosphatidylethanolamine is
principally derived from diacylglyceride. Hence, 18:0 and 16:0
composition of diacylglyceride, phosphatidylethanolamine, and
phosphatidylserine can be used to calculate the activities of
phosphatidylserine decarboxylase and CDP-ethanolamine.
[0117] Other possible assays: Other fatty acids within
phosphatidylserine and diacylglyceride may prove better indices of
flux into phosphatidylethanolamine than 16:0 and 18:0. Examples
include: 18:1, 18:2, 20:4, 22:6. Additionally, the total
concentration of phosphatidylethanolamine is important and might be
used to scale the actual flux of the two contributing pathways.
Example 3
Lecithin-Cholesterol Acyltransferase (LCAT)
[0118] Substrate. Fatty acids on the SN-2 position of phospholipids
and free cholesterol
[0119] Product: Cholesterol ester and lyso-phospholipid
[0120] Location: Plasma, surface of HDL particles
[0121] Function: To solubilize cholesterol in HDL core material for
reverse transport of cholesterol from peripheral tissues back to
liver.
[0122] Synopsis of assay: In general, saturated fatty acids and
monounsaturated fatty acids are esterified to cholesterol by ACAT,
and polyunsaturated fatty acids are esterified to cholesterol by
LCAT. The exception is 18:2, which has complex incorporation
pattern probably related to whether or not it is a dietary
component. The relative contribution of ACAT and LCAT to plasma
cholesterol ester concentrations can be determined by determining
the saturated, monounsaturated, and polyunsaturated fatty acid
composition of plasma cholesterol esters.
[0123] Additionally, if liver cholesterol esters are assayed in
addition to plasma cholesterol esters, the composition of liver
cholesterol esters can be assumed to represent the composition of
cholesterol esters synthesized via ACAT, and the difference between
the plasma and liver cholesterol ester composition can be assumed
to be contributed by the activity of LCAT.
[0124] Furthermore, the composition difference between
phosphatidylcholine and lysophosphatidylcholine can be used to
indicate the fatty acids utilized by LCAT.
[0125] LCAT is one of two enzymes responsible for esterifying fatty
acids to free cholesterol for plasma CE transport. The other
enzyme, ACAT2, is present in the liver and is responsible for
creating the CE that is sent into the blood in VLDL (forward
cholesterol transport), eventually contributing to LDL cholesterol
content. LCAT is presumed to be involved in "good" or reverse
cholesterol transport by mediating the esterification and, thus,
solubilization of free cholesterol from peripheral tissues, which
causes it to migrate into the core of HDL particles. ##STR3##
[0126] By plotting the composition of plasma CE against liver CE,
it is clear that plasma CE contains significantly more 18:2n6 and
20:4n6 in both primates and mice while primates contain high
concentrations of 20:5n3 in plasma CE and mice contain high
concentrations of 22:6n3 in plasma CE. Liver CE is comprised of
much higher concentrations of 16:0, 16:1n7 and 18:0 than plasma,
while the plasma and liver 18:1n9 composition of CE is relatively
equal. Thus a component of CE that is synthesized only by ACAT in
the liver is the saturated fatty acid content of CE.
Dietary Oil Treated Primates
[0127] Plotting the plasma cholesterol ester composition against
liver cholesterol ester composition can be used to determine
selectivity for fatty acid by LCAT or ACAT. Plotting the saturated,
monounsaturated (MUFA) and polyunsaturated fatty acids saturated
fatty acids have a slope of less than 1, MUFA look like unity and
polyunsaturated fatty acids have a slope >1. The only exception
is polyunsaturated fatty acids from corn oil treated primates.
These primates look like 18:2 is esterified to cholesterol ester by
ACAT as well as LCAT. An important feature here is the
polyunsaturated fatty acids from corn oil treated animals do not
fall on the line for the polyunsaturated fatty acids for all other
dietary oils.
Example 4
Analysis of Acyl-CoA Acyltransferase (ACAT2)
[0128] Overview of Assay: When both liver and plasma samples are
available, the concentration of each fatty acid in cholesterol
ester in plasma and liver can be used to determine the percentage
contribution of ACAT and LCAT, respectively, to the total
cholesterol ester concentration of plasma. This can be done because
the composition of cholesterol ester in liver can be assumed to be
derived exclusively from ACAT activity, and because the total
composition of cholesterol ester in plasma must be the sum total of
cholesterol ester produced via ACAT and exported to plasma, and
cholesterol ester produced via LCAT in plasma. Hence, by knowing
any single fatty acid that is substrate for ACAT and not LCAT, the
contribution of ACAT to total plasma cholesterol ester
concentrations can be calculated by calculating the dilution of the
selected fatty acid in the plasma cholesterol ester pool.
[0129] Several assumptions are required for such calculation and
the data selected for comparison preferably are compositional (mole
percentage) data, not quantitative concentration data. Once the
compositional data is used to determine the percentage contribution
of ACAT and LCAT, respectively, to total plasma cholesterol ester
concentrations, the quantitative concentration of cholesterol ester
in plasma can be converted into the quantitative amount produced by
ACAT and the quantitative amount produced by LCAT. Furthermore, the
quantitative amount of cholesterol ester produced via ACAT can be
compared to the cholesterol ester concentration in liver as an
estimate of export efficiency in liver.
Assay Parameters
Knowns:
[0130] Plasma CE composition [0131] Plasma CE concentration [0132]
Liver CE composition [0133] Liver CE concentration. Unknowns:
[0134] Percentage of cholesterol ester derived from LCAT [0135]
Percentage of cholesterol ester derived from ACAT [0136] Rate data
for either ACAT or LCAT [0137] Quantitative flux to cholesterol
ester between liver and plasma. Assumptions:
[0138] The fatty acid component of the plasma cholesterol ester
used for the calculations is present on the cholesterol ester
predominantly as the result of ACAT activity. In an LCAT knockout,
plasma cholesterol ester composition would equal or be similar to
liver cholesterol ester composition while in ACAT knockout, liver
cholesterol ester concentrations would approach zero, and therefore
plasma cholesterol ester composition would not equal liver
cholesterol ester composition.
Analysis Process:
[0139] 1) Selecting the fatty acid or fatty acids for use in the
assay.
[0140] The first step in selecting the fatty acid or fatty acids
for use in this assay is to plot to plasma cholesterol ester
composition (expressed in mole percentage) against the liver
cholesterol ester composition. The fatty acid selected must have a
slope <1, because fatty acids with a slope >1 are present in
plasma due principally to LCAT activity. It is important in this
assay that the fatty acid selected be derived exclusively from ACAT
activity because the assay relies on quantifying the dilution of
that fatty acid in the plasma cholesterol ester composition
relative to the liver cholesterol ester composition. Thus, the
ideal fatty acid chosen for this assay will have a slope closer to
zero than the one, and will be of a sufficiently high concentration
in both liver and plasma cholesterol esters such that the signal
derived from the analysis is reliable.
[0141] 2) Select a fatty acid: presumed not to be substrate for
LCAT, with a slope near zero, and with a sufficiently high
concentration in liver cholesterol esters to provide a good signal
for the assay. (The lowest slope and the highest concentration in
liver both provide the best signal for the assay.)
[0142] 3) Assemble the composition of liver and the composition of
plasma and the absolute concentrations of cholesterol esters in
liver in the absolute concentration of cholesterol esters in
plasma.
[0143] 4) Perform equations as described below to calculate the
percentage of cholesterol esters produced by ACAT, the percentage
of cholesterol esters produced by LCAT, the concentration of
cholesterol esters derived from LCAT, the concentration of
cholesterol esters derived from ACAT, in the ratio of cholesterol
ester in plasma to cholesterol ester in liver. The equation is the
following. If the total saturated fatty acid composition of
cholesterol ester is chosen as the variable (as it is for mice,
primates and humans, because LCAT does not make CE with a saturated
fatty acid composition), then the equation would be plasma CE %
SAT/Liver CE % SAT. This equation calculates the dilution of liver
derived CE into plasm CE because the % SAT in CE produced by LCAT
(in plasma) should be zero.
Metabolic Signatures
[0144] For all equations listed below, values for DG, PA or
(TG/0.667) may be substituted for each other. -(y)=16:0, 18:0, SAT
or a ratio of two of these
PEMT Pathway
Assay measures the percentage of tissue phosphatidylcholine derived
from PEMT PEMT=((% LIVPC(y))-(% LIVDG(y)))/((% LIVPE(y))-(%
LIVDG(y))) [0145] or =1-((% LIVPC(y))-(% LIVPE(y)))/((%
LIVDG(y))-(% LIVPE(y))) [0146] or =1-CDP-CT CDP-Choline Pathway
Assay measures the percentage of tissue phosphatidylcholine derived
from CDP-CT CDP-CT=((% LIVPC(y))-(% LIVPE(y)))/((% LIVDG(y))-(%
LIVPE(y))) [0147] or =1-((% LIVPC(y))-((% LIVDG(y)))/(((%
LIVPE(y))-(% LIVTG(y))) [0148] or =1-PEMT Phosphatidylserine
Decarboxylase (PSDC) Pathway Assay measures the percentage of
tissue phosphatidylethanolamine derived from PSDC PSDC=((%
LIVPE(y))-(% LIVDG(y)))/((% LIVPS(y))-(% LIVDG(y))) [0149] or
=1-CDP-ET [0150] or =1-((% LIVPC(y))-(% LIVPS(y)))/((% LIVDG(y))-(%
LIVPS(y))) CDP-Ethanolamine Pathway Assay measures the percentage
of tissue phosphatidylethanolamine derived from CDP-ET CDP-ET=((%
LIVPC(y))-(% LIVPS(y)))/((% LIVDG(y))-(% LIVPS(y))) [0151] or
=1-PSDC [0152] or =1-((% LIVPE(y))-(% LIVDG(y)))/((% LIVPS(y))-(%
LIVDG(y))) Acyl-CoA Acyltransferase 2 (ACAT2) Assay measures the
percentage of plasma cholesterol esters derived from ACAT2 ACAT2=(%
PLACESAT)/(% LIVCESAT) [0153] or =(% PLACE16:0)/(% LIVCE16:0)
Lecithin: Cholesterol Acyltransferase (LCAT) Assay measures the
percentage of plasma cholesterol esters derived from LCAT
LCAT=1-ACAT2 [0154] or 1-((% PLACESAT)/(% LIVCESAT))
Triacylglyceride Metabolism De novo vs. recycling=(% TGSAT)/0.667
[0155] If value approximates 50%, then most TG is produced de novo
[0156] If value is lower than 50% then recycling of TG-DG is
occurring.
[0157] PLC or PLD contributing to TG biosynthesis PLC/PLD=(%
TGPUFA)-(% TG18:2n6) [0158] If PLC/PLD increases after treatment
there is an increase in PLC or PLD activity. [0159] Check to see if
TG composition reflects PE or PC to determine substrate for PLC or
PLD [0160] Check to see if effect is consistent in DG and/or PA to
determine if it is a PLC or a PLD Other Key Activities in Lipid
Metabolism
[0161] It is believed that the methods described herein can be
adapted to study and characterize the following: [0162]
Diacylglyceride Acyltransferase (DGAT) [0163] Lipoprotein Lipase
(LPL) [0164] Hormone-Sensitive Lipase (HSL) [0165]
Glycerol-3-Phosphate Acytltransferase [0166] Lyso-Phosphatidic Acid
Acyltransferase (LPAT) [0167] Dihydroxyacetone Phosphate
Acyltransferase (DHAP-AT) [0168] Hepatic Lipase [0169] Cardiolipin
Synthase [0170] Phosphatidylinositol Synthase [0171] Fatty acid
Synthase [0172] Delta-9 Desaturase [0173] Delta-6 desaturase [0174]
Delta-5 Desaturase [0175] Elongase
Example 5
Assessing the Biosynthetic Origin of Phosphatidylcholine
[0176] ##STR4## Liver Phosphatidylcholine Synthesis
[0177] Liver phosphatidylcholine (PC) is synthesized by two
pathways: (1) the CDP-choline pathway and (2) the PEMT pathway. The
CDP-choline pathway uses 1,2-DAG and CDP-choline as its substrate,
while the PEMT pathway uses phosphatidylethanolamine and
S-adenosylmethionine or S-adenosylhomocysteine as substrate. Both
1,2-DAG and phosphatidylethanolamine are acylated, meaning that
they already contain the two fatty acids that will comprise the
fatty acid composition of synthesized phosphatidylcholine once it
is converted by the CDP-choline or PEMT pathway. Hence, unless
newly synthesized phosphatidylcholine has its fatty acid
composition remodeled, the composition of phosphatidylcholine
should be a mixture of the fatty acid composition of
phosphatidylethanolamine and 1,2-DAG.
Liver Phosphatidylethanolamine Synthesis
[0178] Liver phosphatidylethanolamine (PE) is synthesized by two
pathways: (1) the CDP-ethanolamine pathway and (2) the
phosphatidylserine decarboxylase pathway. The CDP-ethanolamine
pathway uses 1,2-DAG and CDP-ethanolamine as its substrate, while
the phosphatidylserine decarboxylase pathway uses
phosphatidylserine as substrate. Both 1,2-DAG and
phosphatidylserine are acylated, meaning that they already contain
the two fatty acids that will comprise the fatty acid composition
of synthesized phosphatidylethanolamine once it is converted by the
CDP-ethanolamine or the phosphatidylserine decarboxylase pathway.
Hence, unless newly synthesized phosphatidylethanolamine has its
fatty acid composition remodeled, the composition of
phosphatidylethanolamine should be a mixture of the fatty acid
composition of phosphatidylserine and 1,2-DAG.
Liver 1,2-diacylglyceride Synthesis
[0179] Liver 1,2-diacylglyceride (DAG) is synthesized de novo from
phosphatidic acid. Like PC and PE, DAG is synthesized from
previously acylated phosphatidic acid, and is thus comprised of the
same fatty acids as phosphatidic acid. However, there is a second
biosynthetic pathway that contributes to cellular DAG
concentrations. The hydrolysis of triacylglycerides (TAG) by one of
a number of lipases creates a DAG, and this DAG does not
necessarily share the same composition as phosphatidic acid.
[0180] The saturated fatty acid composition of lipid classes in
mouse liver. TABLE-US-00002 % Total Saturated 16:0 18:0 Other
Phosphatidylcholine 45.8 .+-. 1.7 33.4 .+-. 3.4 11.7 .+-. 2.9 0.7
.+-. 0.4 (PC) Phosphatidylethanol- 40.6 .+-. 2.1 21.9 .+-. 1.6 18.1
.+-. 2.4 0.6 .+-. 0.3 amine (PE) Phosphatidylserine (PS) 47.3 .+-.
3.8 9.0 .+-. 1.9 37.0 .+-. 4.7 1.3 .+-. 0.7 Diacylcglyceride (DG)
32.1 .+-. 5.5 23.6 .+-. 4.1 5.3 .+-. 1.7 3.2 .+-. 1.0
Triacylglyceride (TG) 30.8 .+-. 4.7 27.0 .+-. 4.6 2.2 .+-. 0.9 1.6
.+-. 0.5
[0181] Anywhere there are two pathways contributing to the
synthesis of a glycerolipid the composition of the glycerolipids
should be able to determine the percentage contribution of each
pathway and the total concentration of the lipid should scale the
flux.
[0182] Although phosphatidylcholine synthesis is essential for both
liver function and lipoprotein synthesis and export into plasma,
the relative contribution of the two biosynthetic pathways for
phosphatidylcholine synthesis to each of these processes is not
fully understood. An initial step in the hepatic synthesis of
lipoproteins involves constructing a phospholipid monolayer "skin,"
into which triacylglycerides are inserted. Based on this, it is
believed that markers of alterations in phosphatidylcholine
synthesis can be used to diagnose or predict dysregulations in
liver-blood lipid exchange. Ideally, the markers of hepatic lipid
accumulation would be present in the blood itself, enabling the
facile measurement of liver lipid status in humans from a blood
sample.
[0183] As stated above, liver phosphatidylcholine is synthesized by
two pathways: (1) the CDP-choline pathway and (2) the PEMT pathway.
These pathways use two previously acylated glycerolipids,
1,2-diacylglycerol in the case of the CDP-choline pathway, and
phosphatidylethanolamine in the case of the PEMT pathway, as
substrate for the biosynthesis of phosphatidylcholine. There is
existing evidence that liver phosphatidylcholine synthesized by the
PEMT pathway is comprised of molecular species that differ from the
molecular species of phosphatidylcholine synthesized via the
CDP-choline pathway (DeLong et al., J Biol Chem 274:29683-29688,
1999). It is now demonstrated herein that there are distinct and
compositional differences between 1,2-DAG and
phosphatidylethanolamine, the precursors to the CDP-choline and
PEMT pathway, and that a modulation of either the CDP-choline
pathway or the PEMT pathway produces a modulation of liver and
plasma PC composition in a manner reflective of, and diagnostic
for, the modulation.
[0184] There has never been a clear determination of (1) whether
quantitative changes in liver phosphatidylcholine composition could
diagnose or predict the balance of PEMT vs. CDP-choline activities
in liver, (2) whether this diagnosis or prediction could be made
from the assessment of the composition of plasma or serum lipids,
and (3) whether these assessments could form the basis of
diagnostics or prognostics for phenotypes related to phospholipid
synthesis. The data included herein demonstrate that (1) that the
origin of phosphatidylcholine biosynthesis (liver CDP-choline and
PEMT) can be determined by measuring the composition of liver,
plasma or serum phosphatidylcholine, (2) that the relative
contribution of the CDP-choline and PEMT pathways to liver and
plasma phosphatidylcholine can be determined by taking a simple
ratio of the concentrations of stearic and palmitic acids in
phosphatidylcholine, and that (3) this ratio is diagnostic and
predictive for liver lipid accumulation and the ability of the
liver to mobilize fatty acids, such as arachidonic acid and
docosahexaenoic acid, into plasma.
[0185] Because 1,2 diacylglycerol and phosphatidylethanolamine have
distinct fatty acid compositions, the composition of the resulting
phosphatidylcholine can be used to assess its biosynthetic origin.
Phosphatidylcholine derived from the CDP-choline pathway is rich in
palmitic acid (16:0) while phosphatidylcholine derived from the
PEMT pathway is rich in stearic acid (18:0). Thus, the ratio of
18:0 to 16:0 in PC is an excellent index of the relative
contribution of the CDP-choline and PEMT pathways to total liver
phosphatidylcholine content.
[0186] Other fatty acids found enriched in liver
phosphatidylethanolamine include arachidonic acid (20:4n6),
docosahexaenoic acid (22:6n3) and ether and plasmalogen-linked
fatty acids, while fatty acids found enriched in the 1,2-DAG pool
are oleic acid (18:1n9) and linoleic acid (18:2n6). Each of these
fatty acids, when found in phosphatidylcholine in liver or plasma,
can provide information about the proportion of PEMT pathway
activity to CDP-choline pathway activity contributing to liver
production of phosphatidylcholine.
[0187] The PEMT pathway is important for mobilizing lipid from the
liver into plasma, and genetic alterations in this pathway can lead
to severe liver damage (Waite et al., J Nutr. 132:68-71, 2002).
This liver damage is only partially reversible with the addition of
dietary choline, which increases the activity of the CDP-choline
pathway. Conversely, a less common but significant perturbation of
the CDP-choline pathway can also cause lipid accumulation in the
liver. Thus, if there were an assay to discriminate how much of the
plasma phosphatidylcholine was derived from the hepatic synthesis
of phosphatidylcholine by the CDP-choline pathway versus the PEMT
pathway, and whether a subject had a proper balance of the activity
of these pathways, a researcher or clinician could assess the
propensity for or presence of lipid accumulation in the liver.
[0188] Further, one could evaluate whether any specific
intervention affects the biosynthesis of phosphatidylcholine by
either pathway, and thus use this assay as a diagnostic. An
advantage of this diagnostic would be that an assay of blood lipids
would be informative about liver lipid metabolism, thus avoiding
the need to take a liver biopsy. Additionally, this assay could
determine whether the metabolism of an individual has been shifted,
such that the diagnostic will have prognostic capabilities that
biopsy-oriented diagnostics do not.
[0189] The compositional dissimilarity between phosphatidylcholine
in the liver synthesized from the CDP-choline pathway and
phosphatidylcholine synthesized from the PEMT pathway has been
described previously (DeLong et al., J Biol Chem 274:29683-29688,
1999). It is believed that the majority of plasma
phosphatidylcholine is derived from liver phosphatidylcholine
pools. Certainly this is true for plasma lipids present in very
low-density, intermediate-density and low-density lipoproteins, all
of which are derived from liver lipid export.
[0190] The inventor has discovered that plasma phosphatidylcholine
lipid composition predicts the lipid composition of
phosphatidylcholine in liver with a high degree of confidence.
Thus, this disclosure provides methods of assessing the lipid
composition of liver PC by assessing the lipid composition of serum
PC.
[0191] Measurement of these compounds, either from biological
samples, or in silico (from a table or database) can be, among
other things, used for:
[0192] (1) the assay of the activity of enzymes involved in the
biosynthesis of phosphatidylcholine within the liver;
[0193] (2) the bulk process of phosphatidylcholine biosynthesis
itself;
[0194] (3) the measurement of processes in which
phosphatidylcholine biosynthesis is a component (either as a direct
assay of the process or as a constituent part of a profile to assay
this process);
[0195] (4) phenotypes or the propensity to express a phenotype that
results from or is related to phosphatidylcholine biosynthesis,
such as liver lipid accumulation, liver growth, or regeneration,
hormone metabolism, and the mobilization of essential fatty acids
from the liver in phosphatidylcholine, and
[0196] (5) identification and testing/characterization of compounds
or non-compound influences (such as exercise, dietary changes,
nutritional treatment, and so forth) regarding their ability to
influence (e.g., treat, detect, analyze, ameliorate, reverse,
and/or prevent changes in) phosphatidylcholine biosynthesis or a
phenotype influenced by phosphatidylcholine biosynthesis.
[0197] These measurements can be used to assess individuals or
populations and to assess the results of an intervention, for
instance an intervention by pharmacological, nutritional,
toxicological, environmental, or genomic means. Further, these
markers and profiles can be used to mine, parse, sort, filter, or
otherwise investigate a database of lipid metabolites.
[0198] Although the invention has been described with reference to
the presently preferred embodiment, it should be understood that
various modifications can be made without departing from the spirit
of the invention. Accordingly, the invention is limited only by the
following claims.
* * * * *